In modern electronic systems, analog circuits are primarily used to condition and discretize physical signals, while most of the information processing occurs in the digital domain. The digital abstraction has allowed us to focus on bits as atomic carriers of information, largely ignore analog nuances in the underlying physical signals, and hence scale hierarchical systems toward transistor counts of over 100 billion on a single chip. While this approach has been a key enabler for managing complexity, it has always been scrutinized for its potential inefficiencies. Why don't we prefer to perform an addition by simply connecting two wires carrying analog currents? Similarly, why not compute an integral by collecting charges on a capacitor? This talk will aim to provide some answers to these questions, with the specific focus on domain-specific circuits for machine learning and hardware security. | Boris Murmann is Professor of Electrical Engineering at Stanford University and Fellow in the context of the CAS Research Focus "Physics and Security".